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Efficiency And Productivity Of Norwegian Tax Offices

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Author Info

  • Førsund, Finn R.

    ()
    (Dept. of Economics, University of Oslo)

  • Kittelsen, Sverre A.C

    ()
    (Ragnar Frisch Centre for Economic Research)

  • Lindseth, Frode

    ()
    (The Norwegian Directorate of Taxes)

Abstract

The performance of local tax offices of Norway is studied over a three year period applying Data Envelopment Efficiency analysis and a Malmquist productivity index. The estimates are biascorrected using a bootstrap approach recently developed for DEA models. The results show that bias correction and the construction of confidence intervals give a quite different picture than without bootstrapping. A set of best practice offices is identified for future work on finding explanations for good performance. The productivity development of individual offices is classified into the four categories efficient cost increase, efficient cost savings, inefficient cost savings and inefficient cost increase

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File URL: http://www.sv.uio.no/econ/english/research/unpublished-works/working-papers/pdf-files/2005/Memo-29-2005.pdf
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Bibliographic Info

Paper provided by Oslo University, Department of Economics in its series Memorandum with number 29/2005.

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Length: 29 pages
Date of creation: 14 Nov 2005
Date of revision:
Publication status: Published in National Institute Economic Review, 2006, pages 106-119.
Handle: RePEc:hhs:osloec:2005_029

Contact details of provider:
Postal: Department of Economics, University of Oslo, P.O Box 1095 Blindern, N-0317 Oslo, Norway
Phone: 22 85 51 27
Fax: 22 85 50 35
Email:
Web page: http://www.oekonomi.uio.no/indexe.html
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Keywords: Tax office; productivity; efficiency; scale efficiency; DEA; bootstrap;

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  1. Førsund, Finn R. & Hjalmarsson, Lennart, 1978. "Generalized Farrell Measures of Efficiency: An Application to Milk Processing in Swedish Dairy Plants," Working Paper Series 17, Research Institute of Industrial Economics.
  2. Simar, L. & Wilson, P.W., 1999. "Statistical Inference in Nonparametric Frontier Models: the State of the Art," Papers 9904, Catholique de Louvain - Institut de statistique.
  3. SIMAR, Léopold & WILSON, Paul, 1995. "Sensitivity Analysis to Efficiency Scores : How to Bootstrap in Nonparametric Frontier Models," CORE Discussion Papers 1995043, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  4. Edvardsen, Dag Fjeld & Føsund, Finn R. & Kittelsen, Sverre A.C., 2009. "Far out or alone in the crowd: Classification of selfevaluators in DEA," HERO On line Working Paper Series 2003:7, Oslo University, Health Economics Research Programme.
  5. Edvardsen, Dag Fjeld & Forsund, Finn R., 2003. "International benchmarking of electricity distribution utilities," Resource and Energy Economics, Elsevier, vol. 25(4), pages 353-371, October.
  6. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
  7. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
  8. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
  9. Finn Førsund & Lennart Hjalmarsson, 2004. "Are all Scales Optimal in DEA? Theory and Empirical Evidence," Journal of Productivity Analysis, Springer, vol. 21(1), pages 25-48, January.
  10. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
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